A Faceted Classification Based Approach to Search and Rank Web APIs

  • Authors:

  • Karthik Gomadam;Ajith Ranabahu;Meenakshi Nagarajan;Amit P. Sheth;Kunal Verma

  • Affiliations:

  • kno.e.sis center, Wright State University, Dayton, OH;kno.e.sis center, Wright State University, Dayton, OH;kno.e.sis center, Wright State University, Dayton, OH;kno.e.sis center, Wright State University, Dayton, OH;Accenture Technology Labs, Palo Alto, CA

  • Venue:
  • ICWS '08 Proceedings of the 2008 IEEE International Conference on Web Services
  • Year:
  • 2008

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Abstract

Web application hybrids, popularly known as mashups, are created by integrating services on the Web using their APIs. Support for finding an API is currently provided by generic search engines or domain specific solutions such as Google and ProgrammableWeb. Shortcomings of both these solutions in terms of and reliance on user tags make the task of identifying an API challenging. Since these APIs are described in HTML documents, it is essential to look beyond the boundaries of current approaches to Web service discovery that rely on formal descriptions. In this work, we present a faceted approach to searching and ranking Web APIs that takes into consideration attributes or facets of the APIs as found in their HTML descriptions. Our method adopts current research in document classification and faceted search and introduces the serviut score to rank APIs based on their utilization and popularity. We evaluate classification, search accuracy and ranking effectiveness using available APIs while contrasting our solution with existing ones.